# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for average pooling layers."""

from absl.testing import parameterized
import keras
from keras import combinations
from keras import testing_utils
import tensorflow.compat.v2 as tf


@combinations.generate(combinations.combine(mode=['graph', 'eager']))
class AveragePoolingTest(tf.test.TestCase, parameterized.TestCase):

  def test_average_pooling_1d(self):
    for padding in ['valid', 'same']:
      for stride in [1, 2]:
        testing_utils.layer_test(
            keras.layers.AveragePooling1D,
            kwargs={
                'strides': stride,
                'padding': padding
            },
            input_shape=(3, 5, 4))

    testing_utils.layer_test(
        keras.layers.AveragePooling1D,
        kwargs={'data_format': 'channels_first'},
        input_shape=(3, 2, 6))

  def test_average_pooling_2d(self):
    testing_utils.layer_test(
        keras.layers.AveragePooling2D,
        kwargs={
            'strides': (2, 2),
            'padding': 'same',
            'pool_size': (2, 2)
        },
        input_shape=(3, 5, 6, 4))
    testing_utils.layer_test(
        keras.layers.AveragePooling2D,
        kwargs={
            'strides': (2, 2),
            'padding': 'valid',
            'pool_size': (3, 3)
        },
        input_shape=(3, 5, 6, 4))

    # This part of the test can only run on GPU but doesn't appear
    # to be properly assigned to a GPU when running in eager mode.
    if not tf.executing_eagerly():
      # Only runs on GPU with CUDA, channels_first is not supported on CPU.
      # TODO(b/62340061): Support channels_first on CPU.
      if tf.test.is_gpu_available(cuda_only=True):
        testing_utils.layer_test(
            keras.layers.AveragePooling2D,
            kwargs={
                'strides': (1, 1),
                'padding': 'valid',
                'pool_size': (2, 2),
                'data_format': 'channels_first'
            },
            input_shape=(3, 4, 5, 6))

  def test_average_pooling_3d(self):
    pool_size = (3, 3, 3)
    testing_utils.layer_test(
        keras.layers.AveragePooling3D,
        kwargs={
            'strides': 2,
            'padding': 'valid',
            'pool_size': pool_size
        },
        input_shape=(3, 11, 12, 10, 4))
    testing_utils.layer_test(
        keras.layers.AveragePooling3D,
        kwargs={
            'strides': 3,
            'padding': 'valid',
            'data_format': 'channels_first',
            'pool_size': pool_size
        },
        input_shape=(3, 4, 11, 12, 10))

if __name__ == '__main__':
  tf.test.main()
